CA3117928C

CA3117928C - Retail deployment model

Info

Publication number: CA3117928C
Application number: CA3117928A
Authority: CA
Inventors: Sharon Rossmark; Larry Kobori; Gary Kerr
Original assignee: Allstate Insurance Co
Current assignee: Allstate Insurance Co
Priority date: 2006-02-15
Filing date: 2006-09-27
Publication date: 2023-11-28
Anticipated expiration: 2026-09-27
Also published as: CA3117928A1; CA2541763A1; US20150088566A1; CA2561195A1; US11232379B2; US8938432B2; US20070192347A1; US20220398510A1

Abstract

A method of determining and optimizing the location of a new insurance agency is disclosed to increase market penetration of underrepresented markets. The method comprises the use of a scoring algorithm to rank various geographic regions or related zip codes. The scoring algorithm may be implemented by a location modeling system based on variables selected by a user.

Description

RETAIL DEPLOYMENT MODEL
Field of the Invention The present invention relates to business location modeling systems and methods. More particularly, the invention relates to insurance agency location modeling to establish new insurance agency locations in various geographic locations based on an evaluation of user selected criteria.
Description of the Related Art The decision to open a new office or branch in order to increase sales for various different types of products or services in a particular geographical region or postal zip code can involve consideration of numerous factors such as population density, potential population growth, customer household data, and traffic flow patterns. When determining a location for a new office or branch for an insurance company, a business entity or business owner may desire to consistently use the same factors or analysis when comparing different geographical locations for the new office site. The use of inconsistent data or factors across geographic locations may result in a suboptimal site location being selected for a new office or branch.
Moreover, as the number of potential geographic regions increases, it can be desirable to normalize results so that comparisons between the different geographic regions may be utilized.
For example, a company providing a particular product or service may wish to open a number of new offices or branches across a large geographic region such as the United States. With such a large geographic region to consider, it can be desirable to display comparable results to decision makers so that suitable site locations may be selected.
Current site location models in use in other industries such as retail pharmacy do not take into account unique factors and problems found in the insurance industry. In addition, existing site location models or systems of other industries may not utilize an overall scoring method that allows results to be consistently and easily displayed to the decision maker or business entity.
Without an overall scoring methodology, the analysis of the results is more time consuming and inefficient involving the unnecessary consumption of numerous resources.

Date Recue/Date Received 2021-05-10 Therefore, there is a need in the art for an insurance agency location modeling method and system regarding the process of determining successful placement of future insurance agency locations. The method and system for suitable insurance agency locations must provide consistent and easily interpreted results.
Summary Aspects of the present invention overcome problems and limitations of the prior art by providing a method of determining suitable locations for new insurance agency locations. The disclosed method may be utilized to increase market penetration of underrepresented markets.
The method comprises the use of a scoring algorithm to rank various geographical regions by related zip codes. The scoring algorithm may be implemented by a location modeling system based upon markets selected by a user.
In an exemplary aspect of the invention, a user may select a geographical region to be evaluated for placement of an insurance agency location. The geographical region may be in the form of a postal zip code. Various modeling factors are used to determine a highly suitable location for the new insurance agency. A score for each zip code is calculated with the highest overall score representing the most highly suitable, preferred or optimized location for the new office or branch.
In certain embodiments of the invention, the present invention can be partially or wholly implemented with a computer-readable medium, for example, by storing computer-executable instructions or modules, or by utilizing computer-readable data structures. Of course, the methods and systems of the above-referenced embodiments may also include other additional elements, steps, computer-executable instructions, or computer-readable data structures.
The details of these and other embodiments of the present invention are set forth in the accompanying drawings and the description below. Other features and advantages of the invention will be apparent from the description and drawings, and from the claims.

2 Date Recue/Date Received 2021-05-10 Brief Description of the Drawings The present invention may take physical form in certain parts and steps, embodiments of which will be described in detail in the following description and illustrated in the accompanying drawings that faun a part hereof, wherein:
Figure 1 shows a diagram of a computer system that may be used to implement aspects of the invention.
Figure 2 illustrates a method of application of the insurance agency location modeling system, in accordance with an embodiment of the invention.
Figure 3 illustrates an exemplary user interface screen for a section of the agency deployment modeling system, in accordance with an aspect of the invention.
Figure 4 illustrates an exemplary user interface screen enabling a user to select various geographic regions, in accordance with an aspect of the invention.
Figure 5 illustrates the selection of a predefined template, in accordance with an aspect of the invention.
Figures 6a, 6b, and 7 illustrate the calculation of a final score for selected zip codes, in accordance with an aspect of the invention.
Figure 8 illustrates the display of the final score along with additional profile information associated with the particular zip code, in accordance with an aspect of the invention.
Figure 9 illustrates a map in which a particular zip code may be viewed by a user, in accordance with an aspect of the invention Detailed Description Exemplary Operating Environment Figure 1 shows a diagram of a computer system that may be used to implement aspects of the invention. A plurality of computers, such as research workstations 102 and 104, may be

3 Date Recue/Date Received 2021-05-10 coupled to a user computer 112 via networks 108 and 118. User computer 112 may be coupled to a data solutions transaction manager computer 110, which is described in detail below. User computer 112 provides decision makers with a user interface on user workstations 112, 114 and 116 for displaying policy information and decisions such as potential new agency locations, and enables users to interact with data solutions transaction manager computer 110.
User workstations 112, 114 and 116 and research workstations 102 and 104 may require information from external data sources to assist evaluation of a potential new agency location.
Requests for such information may be transmitted via data solutions transaction manager computer 110 to a data gathering system 120. Data gathering system 120 may include a processor, memory and other conventional computer components and may be programmed with computer-executable instructions to communicate with other computer devices.
Data gathering system 120 may access external sources of information, such as information vendors 122, 124 and 126 via the Internet 128. Information vendors may include federal or state agencies that provide aggregate motor vehicle data, census information, or vendors that provide demographic information, maps and geographical location information, and other information that may be used to evaluate potential agency locations.
Data solutions transaction manager 110 may be programmed with computer-executable instructions to receive requests for data from user computers 112, 114 and 116 and research workstations 102 and 104, format the requests and transmit the requests to data gathering system 120. In one embodiment of the invention, requests for data are in the form of documents that are in extensible markup language (XML) format. Data solutions transaction manager 110 may also be coupled to a data manager computer device 130 that accesses customer data stored in a data repository 132. In one embodiment of the invention, all data gathered on a customer or potential customer is stored in data repository 132 so that when additional requests are made for the same data, the data may quickly be obtained without requesting it from information vendors 122, 124 and 126. Data repository 132 may be implemented with a group of networked server computers or other storage devices.
Decision makers may be provided with a user interface on user computers 112, 114 and 116 for displaying policy information and decisions, and enables users to interact with data solutions transaction manager 110. The user interface may allow a user or decision maker to

4 Date Recue/Date Received 2021-05-10 perform a variety of functions, such as entering local market data into analysis report templates, and displaying decision results. In addition, users may execute various analysis tools to answer questions such as: 1) "Where is the best location for a new office?", 2) "What is the makeup of the population?", 3) "Where are our competitors' offices?", 4) "Which markets will experience household and vehicle growth?", and 5) "Are there enough prospects that own homes in a three mile radius around a particular agent's office?"
In an embodiment, senior decision makers may use the system to improve their understanding of the marketplace, facilitating business decisions. The user may select various geographic regions and run various reports to obtain agency deployment information.
One or more of the computer devices and terminals shown in Figure 1 may include a variety of interface units and drives for reading and writing data or files.
One skilled in the art will appreciate that networks 108, 118 and 128 are for illustration purposes and may be replaced with fewer or additional computer networks. One or more networks may be in the form of a local area network (LAN) that has one or more of the well-known LAN topologies and may use a variety of different protocols, such as Ethernet. One or more of the networks may be in the form of a wide area network (WAN), such as the Internet. Computer devices and other devices may be connected to one or more of the networks via twisted pair wires, coaxial cable, fiber optics, radio waves or other media.
The term "network" as used herein and depicted in the drawings should be broadly interpreted to include not only systems in which remote storage devices are coupled together via one or more communication paths, but also stand-alone devices that may be coupled, from time to time, to such systems that have storage capability. Consequently, the term "network" includes not only a "physical network" but also a "content network," which is comprised of the data¨
attributable to a single entity¨which resides across all physical networks.
Exemplary Embodiments Figure 2 illustrates a method of determining a suitable location of an insurance agency location in an embodiment of the invention. The method may be implemented by a location modeling system being executed on a computer such as data solutions transaction manager 110.
Date Recue/Date Received 2021-05-10 The method of Figure 2 will be illustrated in the following exemplary embodiment. Figure 3 illustrates a user interface screen 302 that may be presented to a user by the data solutions transaction manger 110. The user interface screen 302 may enable a user to execute a number of different analysis tools such as agency deployment tool 304, a report generation tool 306, a local market analysis tool 308, atlas tools 310 and 312, and/or a library of generated reports tool 314.
A user may execute the agency deployment tool 304 by clicking on the agency deployment box.
Upon activation of the agency deployment tool 304, in a first step 202, a user selects at least one geographic region to be evaluated for placement of a new insurance agency location.
The geographic region may be a region of the United States such as the Midwest or may be a combination of various different states, cities, towns, neighborhoods, or other geographic identifiable regions. Those skilled in the art will realize that numerous different geographic regions and combinations may be defined for analysis. For instance, Figure 4 illustrates a user interface screen 402 that enables a user to select various U.S. States for analysis based on selection box 403.
A user may create a customized geographic region for ease of use in future sessions. For example, a user may select California, Florida, Illinois, New York, Ohio, and Texas using the add button 404 and define these selected States (405) as the "Large States"
406. Similarly, a user may edit their customized selection through the use of the remove button 407. A user may save their customized selection using the "Save Changes" button 408. Once saved, a user may select their customized selection during future modeling session as illustrated in Figure 5 in the "Choose Your Geography" selection screen 502.
Based on the user selected geographic regions, the underlying or related zip codes for selected geographic regions are determined in step 204. The use of zip codes enables all of the collected data from various data sources to be converted into data that may be used and scored on a common metric scale. The common metric scale allows various information sources to be integrated and scored. Those skilled in the art will realize that distinguishable data other than zip codes may be used in order to allow processing of data on a common metric scale.
Next, in step 206, data is received from the user which includes at least one modeling factor to be utilized in the determination of the insurance agency location.
Those skilled in the Date Recue/Date Received 2021-05-10 art will realize that any number or combination of modeling factors may be used depending upon the marketing or agency growth strategy.
The modeling factors may include one of the following exemplary factors: 1) households with 2+ vehicles current year estimate; 2) households with 2+ vehicles five year projection; 3) net change vehicle households in five years; 4) owner occupied dwellings current year estimate;

5) owner occupied dwellings five year projection; 6) net change in owner occupied dwellings in five years; 7) total households current year estimate; 8) total household five year project; 9) net change (number and %) in households in five years; 10) new movers; 11) new homeowners; 12) average household net worth; 13) average household income; 14) population 25+
years old; 15) population 25+ with some college education; 16) population 25+ with associate degree; 17) population 25+ with bachelor's degree; 18) population 25+ with graduate or professional degree;
19) percent population 25+ any college education; 20) households with length of residence less than one year; 21) percent households with length of residence less than one year; 22) active property insurance casualty policies; 23) active life/financial insurance policies; 24) active insurance policies; 25) total insurance customer households; 26) total insurance customer household.lifetime value; 27) average insurance customer household lifetime value; 28) value of expansion opportunity; and 29) new businesses.
As those skilled in the art will realize, the above modeling factors and/or combinations of modeling factors do not represent an exhaustive list of modeling factors that may used in the determination of agency locations. As an alternative, to the individual selection of each of the modeling factors, templates may be defined with particular modeling factors to be used in the agency location model. For example, templates such as "Established but Still Growing"
template 504 in Figure 5, and a "Communities in Progress" template 506 may be selected from a group of preexisting templates. Each template may contain modeling factors that have been proven to be statistically important when trying to identify particular growth opportunities such as finding markets that have existing neighborhoods that are still growing.
The following factors may be preselected to be used with the "Established but Still Growing"
template 504: 1) net change (number and %) in households in five years; 2) percent population 25+
years old with any college education; 3) percent households with length of residence less than one year; 4) total insurance customer households; and 5) average insurance customer household lifetime value.

Date Recue/Date Received 2021-05-10 Average insurance customer household lifetime value may be calculated by subtracting projected expenses for a customer from projected revenue for each calendar year over a time span of a projected retention period. These values may then be averaged to compute the average insurance customer lifetime value. These are calculated and accessible for use in the model via research network 108.
In another example, the "Communities in Progress" template 506 may identify growth opportunities in generally smaller communities experiencing recent change.
Modeling factors that may be utilized when the "Communities in Progress" template 506 is used may include: 1) new movers; 2) new homeowners; 3) percent households with length of residence less than one year; and 4) new businesses.
In step 208, a final score per zip code may be calculated. The calculation of the scores may be determined by the following equations:
Variablel information ¨ Variablel t = Variablel score Variable 1 a Equation 1 (Variable 1 score * Variable 1 weight) + (Variable 2 score * Variable 2 weight) +
(Variable 3 score * Variable 3 weight) + other Variables = Composite score Equation 2 Composite Score - =Final Score a Equation 3 In equations 1 and 3, la represents the mean and a represents standard deviation of the individual variables and variable scores multiplied by their variable weights.
A positive score reflects greater potential for future business growth in the particular geographic region of interest. A negative score reflects less opportunity for future growth relative to the variation within each geographic region. For example, Figures 6a, 6b, and 7 illustrate the calculation of a Date Recue/Date Received 2021-05-10 final score for zip codes in a state, "zips 001 to 003" 602, "zips007, 009, 011, 013, and 016"
604, and "zip050" 606. Each of the zip codes represents a geographic region selected by the user for evaluation. In Figure 6a, six variables are modeled to identify growth opportunities for placement of insurance agency locations. Variable information 609 for each of the zip codes listed 602, 604, and 606 is shown in Table 1 of Figure 6a. The variable information includes counts, dollars, and percentage information for the six modeling factors.
A score per variable 617 using equation 1 is calculated for each of the zip codes listed 602, 604, and 606 as shown in Table 2 of Figure 6a. Table 3 illustrates that a range of weighting factors 621 may be applied to each of the variables. Those skilled in the art will realize that different ranges of weighting factors may be used for each of the modeling factors and that the weighting factors may change over time and with use of model. The weighting factors may be adjusted so that a particular modeling factor is given more significance in the calculation of the final score. In the examples of Figure 6b, each variable can be assigned equal or varying weights. Table 4, using equation 2, illustrates zip codes 602, 604, and 606 with equal weights.
The calculated composite score for "zip 001" 602 is 0.802451 (616), "zip007"
604 is 0.297420 (618), and "zip050" 606 is 0.677538 (620). Table 5 illustrates these same zip codes 602, 604, and 606 with varying weights. Table 5 lists the calculated composite score for "zip 001" 602 is 0.90198781 (680), "zip 007" 604 is 0.34198808 (682), and "zip 050" 606 is 0.87358715 (684).
Next, equation 3 is applied to each of zip codes 602, 604, and 606 as illustrated in Tables 1 and 2 of Figure 7. For example Table 1 of Figure 7, calculates the Final Score using equal weights for "zip001" 602 is 1.728691 (690), "zip007" 604 is 0.64072 (692), and "zip050" 606 is 1.459595 (693). Table 2 illustrates the calculated Final Score using varying weights for zips 602, 604, 606. Figure 7 zip code examples are based upon actual information for the state of Delaware. The positive scores reflect greater potential for future business growth in the particular geographic region of interest; whereas, the negative scores reflect less opportunity for future growth relative to the variation within each geographic region.
Finally, the zip codes are ranked and compared in step 210 according to their value 702, 706, and 704 (uses equal weights); 750, 770, and 760 (uses varying weights).
The final scores for each zip code may be displayed along with additional profile information which may be of interest to the user. For example, the final scores may be Date Recue/Date Received 2021-05-10 integrated with profile information to create new perspectives and insights regarding each market. An example of such profile information is illustrated in Figure 8. In Figure 8, a zip code "802" along with its associated Final Score of 6.93 (804) is shown with profile information such as number of households in 2003 (806) and percentage of college education (808). Other profile information that may be displayed includes rccent change information, projected growth number, percent current insurance penetration, number of prospects, current number and type of insurance agencies, and number of competitor insurance agencies. Profile information is periodically updated (annually, bi-annually, quarterly, or biweekly).
Any of the selected zip codes may be displayed on a map such that specific point locations and surrounding areas may be interactively defined with respective model outputs and information generated for surrounding areas. For example, Figure 9 illustrates a map in which a particular zip code is illustrated by the region defined at 902. In addition, user defined map features may display information such as model outputs, competitor agency locations, and other useful information. The maps may also contain three-dimensional aerial imagery and other geographic features (cartography) which may be displayed to the user. The integration of the results of the final scores along with additional information such as competitor agency locations and cartography may enable a user to pinpoint a highly suitable potential location for the new agency in a particular neighborhood at a particular street address. In addition, reports may be generated detailing the scores for each of the selected zip codes or geographic regions along with detailed maps of each of these potential new agency locations.
A few examples of a few embodiments of the invention are provided below. These examples describe only versions of a few embodiments of the invention. The invention is not limited to the examples described below and includes numerous additional embodiments and versions. The examples should not be read to limit the disclosure of the invention in this application.
Example 1 An insurance location is determined through steps of (1) receiving from a user at least one geographic region to be evaluated for placement of the insurance agency location, (2) based on the at least one geographic region received in step (1), determining related zip codes to be Date Recue/Date Received 2021-05-10 evaluated, (3) receiving from the user at least one modeling factor to be utilized in the determination of the insurance agency location, (4) calculating at a processor a final score for each of the zip codes determined in step (2); and (5) comparing the final scores for each of the zip codes to determine the zip code with the highest final score The receiving, determining, calculating and comparing can be performed by a computer. They also can be performed by a person. In addition, the modeling factors that can be used include one or more of the following:
total and net change in households in current year and last five years; number of new homeowners and new movers; percentage of population with at least twenty five years of age and some college education; percentage of households with length of residency of less than one year; total number of agency customer households; total number of new businesses; agency customer household lifetime value; whether or not household maintains 2 or more vehicles;
whether a dwelling is owner occupied; average household income and average household net worth.
Example 2 The location for an insurance agency is determined using at least the following steps. A
geographic region to be evaluated for placement of the insurance agency location is received from a user. Based on this geographic region, particular zip codes are identified to be evaluated.
A composite score is calculated for each zip code. A final score is then calculated at a processor for each of the zip codes using the formula Composite Score -It Final Score.
The final scores are compared to each other to determine the relative ranking.
The final scores may be displayed on a map and/or summarized and detailed in a report.
Example 3 A computer-readable medium contains computer-executable instructions for causing a computer device to perform a number of steps. These steps include (a) receiving from a user zip Date Recue/Date Received 2021-05-10 codes to be evaluated for placement of an insurance agency location; (b) receiving from research terminal 102, 104 modeling factors to be utilized in the determination of the insurance agency location; (c) calculating at a processor a final score for each of the zip codes received in step (a);
(d) comparing the final scores for each of the zip codes to determine the zip code with the highest final score; and (e) displaying the final scores for each of the zip codes on a map and/or report that contains at least street level information.

Date Recue/Date Received 2021-05-10

Claims

We claim:

1. A
method of operating an agency deployment tool in a computer system having a user computer, a data solutions transaction manager computer, and a network coupling the user computer and the data solutions transaction manager computer, the method comprising:
(a) receiving at a graphical user interface of the user computer a plurality of geographical regions, each geographical region associated with at least one postal code;
(b) transmitting, over the network, from the user computer to a processor of the data solutions transaction manager computer, the plurality of geographical regions;
(c) determining, at the processor, at least two postal codes representing the plurality of geographical regions, the at least two postal codes representing a common metric scale for evaluating placement of an insurance agency location, each one of the at least two postal codes representing one of the plurality of geographic regions;
(d) receiving, over the network, at the processor, at least one modeling factor to be utilized in the determination of the insurance agency location, the modeling factor received from the user computer and representing data on a per postal code level for each of the at least two postal codes, wherein the at least one modeling factor includes a five year projection of a number of owner-occupied dwellings;
(e) assigning, at the processor, weights to the at least one modeling factor for each of the at least two postal codes;
(f) obtaining, by the data solutions transaction manager computer, customer data corresponding to the plurality of geographical regions, the customer data including current customer data and potential customer data;
(g) calculating at the data solutions transaction manager computer a score representative of a desirability for placement of the insurance agency location for each of the at least two postal codes, wherein calculating the score comprises:
determining a value of a demographic information variable for a respective postal code;
determining a mean and a standard deviation for the demographic information variable based on demographic information, the demographic information obtained from the customer data; and calculating the score using the value, the mean, and the standard deviation of the demographic information variable;
(h) comparing at the data solutions transaction manager computer the score for each of the at least two postal codes;

Date Recue/Date Received 2022-09-29 (i) transmitting, from the data solutions transaction manager computer, the score for each of the at least two postal codes to the user computer over the network;
and (j) displaying the score for each of the at least two postal codes on a map rendered via the graphical user interface of the user computer.

2. The method of claim 1, wherein the map includes street level information.

3. The method of claim 1, wherein step (g) further comprises the steps of:
calculating a composite score for each of the at least two postal codes;
and (ii) calculating a final score for each of the at least two postal codes based on the equation Composite Score - j.t = Final Score, a wherein tt represents the mean and a represents the standard deviation of the composite score for each of the at least two postal codes.

4. The method of claim 3, wherein the composite score comprises a weighted composite score.

5. The method of claim 1, wherein the at least one modeling factor includes a percentage of households with length of residency of less than one year.

6. The method of claim 1, wherein the at least one modeling factor includes a total number of agency customer households.

7. The method of claim 1, wherein the at least one modeling factor includes a total number of new businesses.

8. The method of claim 1, wherein the at least one modeling factor includes households with two or more vehicles.

Date Regue/Date Received 2022-09-29

9. The method of claim 1, wherein the at least one modeling factor comprises average household income and average household net worth.

10. A method of operating an agency deployment tool in a computer system having a user computer, a data solutions transaction manager computer, and a network coupling the user computer and the data solutions transaction manager computer, the method comprising:
(a) receiving, at a graphical user interface of the user computer, at least one geographical region, the at least one geographical region associated with a plurality of postal codes;
(b) transmitting, over the network, at a processor of the data solutions transaction manager, the at least one geographic region, from the user computer;
(c) based on the received at least one geographic region received in step (b), determining at the processor related postal codes representing the at least one geographical region to be evaluated, the postal codes representing a common metric scale;
(d) receiving, over the network, at the processor modeling factors from the user computer, the modeling factors representing data on a per postal code level for each of the related postal codes, wherein at least one of the received modeling factors includes a five year projection of a number of owner-occupied dwellings;
(e) assigning at the processor weights to the modeling factors for each of the related postal codes;
(f) obtaining, by the data solutions transaction manager computer, customer data corresponding to the at least one geographical region, the customer data including current customer data and potential customer data;
(g) calculating at the data solutions transaction manager computer a score representative of a desirability for placement of the insurance agency location for each of the related postal codes, wherein calculating the score comprises:
determining a value of a demographic information variable for a respective postal code;
determining a mean and a standard deviation for the demographic information variable based on demographic information, the demographic information obtained from the customer data; and calculating the score using the value, the mean, and the standard deviation of the demographic information variable;
(h) ranking at the processor the scores for each of the related postal codes;
Date Recue/Date Received 2022-09-29 (i) transmitting, from the processor, the score for each of the related postal codes to the user computer over the network; and (j) displaying the score for each of the related postal codes on a map rendered via the graphical user interface of the user computer.

11. A method for operating an agency deployment tool in a computer system having a user computer, a data solutions transaction manager computer, and a network coupling the user computer and the data solutions transaction manager computer, the method comprising:
(a) receiving at a graphical user interface of the user computer a geographical region to be evaluated for placement of an insurance agency location, the geographical region associated with a plurality of postal codes;
(b) transmitting, over the network, at a processor of the data solutions transaction manager computer, the geographical region, from the user computer;
(c) determining at the data solutions transaction manager computer postal codes representing the received geographical region, the postal codes representing a common metric scale for evaluation of the placement;
(d) gathering, over the network, data associated with the determined postal codes;
(e) selecting a template having various predetermined modeling factors to be utilized in the evaluation of the insurance agency location, the modeling factors representing data on a per postal code level, wherein at least one of the predetermined modeling factors includes a five year projection of a number of owner-occupied dwellings;
(f) assigning, at the processor, weights to the modeling factors;
(g) calculating a final score for each of the determined postal codes at the data solutions transaction manager computer, the final score for each of the determined postal codes calculated using the data associated with the postal codes and the modeling factors;
(h) transmitting, from the data solutions transaction manager computer, the final score for each of the determined postal codes to the user computer over the network;
and (i) displaying the final score for each of the determined postal codes on a display via the graphical user interface of the user computer.

12. The method of claim 11, wherein step (g) further comprises the steps of:
calculating a variable score; and (ii) calculating a composite score, wherein calculating a final score for each postal code is based on the equation Date Regue/Date Received 2022-09-29 Composite Score - ji = Final Score, wherein j.t represents the mean and a represents the standard deviation of the composite score for each of the postal codes.

13. The method of claim 12, wherein the composite score comprises a weighted composite score.

14. The method of claim 11, wherein the modeling factors further comprise net change in number and percentage of households in the next five years, percentage of households with length of residency less than one year, and total insurance company customer households.

15. The method of claim 11, wherein the modeling factors further comprise a percentage of households with length of residency less than one year or recent change in number of households and new businesses.

16. The method of claim 11, wherein the display also includes additional modeling factors, profile information, existing agency locations, and competitor locations.

17. The method of claim 11, wherein the display also includes a map having aerial imagery.

18. The method of claim 17, wherein the map is a thematic map.

19. The method of claim 11, wherein the display includes the use of 3D
cartography.

20. The method of claim 11, wherein the display comprises a map of specific point locations and surrounding areas that are defined with respective model outputs and information generated for the surrounding areas.

21. A method of operating an agency deployment tool in a computer system having a user computer, a data solutions transaction manager computer, and a network coupling the user computer and the data solutions transaction manager computer, the method comprising:

Date Regue/Date Received 2022-09-29 (a) receiving at a graphical user interface of the user computer a geographical region to be evaluated for placement of an insurance agency location, the geographical region associated with a plurality of postal codes;
(b) transmitting, over the network, at a processor of the data solutions transaction manager computer the geographical region from the user computer associated;
(c) determining at the data solutions transaction manager computer postal codes representing the received geographical region, the postal codes representing a common metric scale for evaluating the placement of the insurance agency location;
(d) gathering over the network data associated with the determined postal codes;
(e) selecting a template having at least one modeling factor to be utilized in the evaluating of the placement of the insurance agency location, the at least one modeling factor representing data on a per postal code level, wherein the at least one modeling factor includes one or more of:
a number of new homeowners and new movers, a current year estimate of households with two or more vehicles, a five year projection of the households with the two or more vehicles, a net change in the households that own the vehicles within five years, a current year estimate of a number of owner-occupied dwellings, a five year projection of the number of owner-occupied dwellings, a net change in the owner-occupied dwellings in five years, a current year estimate of a total number of households, a five year projection of the total number of households, a net change in the total number of households in five years, an average household net worth, an average household income, number of people at least twenty-five years old, number of people at least twenty-five years old with some college education, number of people at least twenty-five years old with an associate's degree, number of people at least twenty-five years old with a bachelor's degree, number of people at least twenty-five years old with a professional degree, percent of population at least twenty-five years old with any college education, a number of households with length of residence less than one year, percent of households with the length of residence less than one year, number of active property insurance policies, number of active life or financial insurance policies, number of active insurance policies, total number of customer households, total insurance customer household lifetime value, average customer household lifetime value, value of expansion opportunity, and number of new businesses;

Date Regue/Date Received 2022-09-29 (f) assigning weights to the at least one modeling factor for each of the determined postal codes;
(g) calculating at the data solutions transaction manager computer a final score representative of a desirability for the placement of the insurance agency location for each of the postal codes determined in step (c) using the data associated with the determined postal codes and the at least one modeling factor;
(h) comparing at the data solutions transaction manager computer the final scores for each of the postal codes;
(i) transmitting, from the data solutions transaction manager computer, the final scores for each of the postal codes to the user computer over the network; and (j) displaying the calculated final scores on a display via the graphical user interface of the user computer.

22. The method of claim 21, wherein step (g) further comprises the steps of:
calculating a variable score; and (ii) calculating a composite score, wherein calculating the final score for each postal code is based on the equation Composite Score ¨ it = Final Score, wherein 1.1 represents the mean and a represents the standard deviation of the composite score for each of the postal codes.

23. The method of claim 22, wherein the composite score comprises a weighted composite score.

24. The method of claim 21, wherein the display also includes additional modeling factors, profile information, existing agency locations, and competitor locations.

25. The method of claim 21, wherein the display also includes a map having aerial imagery.

26. The method of claim 25, wherein the map is a thematic map.

Date Regue/Date Received 2022-09-29

27. The method of claim 21, wherein the display includes the use of 3D
cartography.

28. A system for operating an agency deployment tool, the system comprising:
a user computer having a processor, a graphical user interface and a display;
a data solutions transaction manager computer having a processor; and a network coupling the user computer and the data solutions transaction manager;
wherein the user computer is configured for:
receiving as input at the graphical user interface a plurality of geographical regions, each one of the geographical regions associated with at least one postal code;
transmitting the plurality of geographical regions to the data solutions transaction manager via the network; and transmitting at least one modeling factor representing data on a per postal code level and comprising a five year projection of a number of owner-occupied dwellings;
wherein the data solutions transaction manager is configured for:
receiving the plurality of geographical regions and the at least one modeling factor from the user computer;
determining at least two postal codes representing the plurality of geographical regions, the at least two postal codes representing a common metric scale, each one of the at least two postal codes representing one of the plurality of geographic regions;
assigning weights to the at least one modeling factor for each of the at least two postal codes;
obtaining, by the data solutions transaction manager computer, customer data corresponding to the plurality of geographical regions, the customer data including current customer data and potential customer data;
calculating at the data solutions transaction manager computer a score representative of a desirability for placement of the insurance agency location for each of the at least two postal codes, wherein calculating the score comprises:
determining a value of a demographic information variable for a respective postal code;
determining a mean and a standard deviation for the demographic information variable based on demographic information, the demographic information obtained from the customer data; and calculating the score using the value, the mean, and the standard deviation of the demographic information variable; and Date Regue/Date Received 2022-09-29 transmitting the score to the user computer;
wherein the user computer is further configured for:
receiving the score for each of the at least two postal codes from the data transactions manager; and displaying, on the graphical user interface, the score for each of the at least two postal codes on a rendered map.

Date Regue/Date Received 2022-09-29